Literature DB >> 34286199

What can we learn from supermarkets? An application of the Poisson distribution (order-up-to) model to improve blood culture bottle supplies.

Fawz Kazzazi1, Diana Kazzazi2, Kishore Kukendra-Rajah3, Marina Basarab4.   

Abstract

BACKGROUND: The order-up-to inventory model is a method for identifying and maintaining the optimal product level for items that that hold value over time and have recurring demand. Typically, supermarkets utilise it to manage stock-levels of non-perishable goods. LOCAL PROBLEM: This project aimed to improve blood culture bottle supplies following reports by junior doctors of shortages when dealing with septic/unwell patients.
METHODS: Data regarding blood culture bottle use was acquired from four hospitals within one trust in London (245 wards). The mathematical 'order-up-to' inventory model (an iterative Poisson distribution) was applied to the 6 months' data.
INTERVENTIONS: The model found three predictable levels of demand to stock wards with no shortages in 99.3% of circumstances (based on historical data). Wards were stocked with blood culture bottles as per their required demand.
RESULTS: A collection method and infrastructure was designed to implement the new policy and was applied to a London tertiary centre. A review of doctors, nurses and ward-managers found significant improvements in supply with no shortages since the model was applied. Issues with the dataset were identified for intensive therapy unit / high dependency unit.
CONCLUSIONS: The 'order-up-to' inventory model provides a useful tool within hospitals for improving stock levels of blood cultures bottles and with that the satisfaction of trainees and patient safety. © Royal College of Physicians 2021. All rights reserved.

Entities:  

Keywords:  blood culture bottles; modelling; stock; supply

Year:  2021        PMID: 34286199      PMCID: PMC8285141          DOI: 10.7861/fhj.2020-0120

Source DB:  PubMed          Journal:  Future Healthc J        ISSN: 2514-6645


  10 in total

1.  Supply chain dynamics in healthcare services.

Authors:  Cherian Samuel; Kasiviswanadh Gonapa; P K Chaudhary; Ananya Mishra
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2.  The sepsis six and the severe sepsis resuscitation bundle: a prospective observational cohort study.

Authors:  Ron Daniels; Tim Nutbeam; Georgina McNamara; Clare Galvin
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3.  Strategic information technology alliances for effective health-care supply chain management.

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4.  Recognition and management of sepsis by junior doctors.

Authors:  Sarah L Cowan; Jonathon Aa Holland; Ian Frost; Andrew D Kane
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Authors:  Michael D Howell; Andrew M Davis
Journal:  JAMA       Date:  2017-02-28       Impact factor: 56.272

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Authors:  Stig Lønberg Nielsen
Journal:  Dan Med J       Date:  2015-07       Impact factor: 1.240

7.  Surviving Sepsis Guidelines: A Continuous Move Toward Better Care of Patients With Sepsis.

Authors:  Daniel De Backer; Todd Dorman
Journal:  JAMA       Date:  2017-02-28       Impact factor: 56.272

Review 8.  Surviving the first hours in sepsis: getting the basics right (an intensivist's perspective).

Authors:  Ron Daniels
Journal:  J Antimicrob Chemother       Date:  2011-04       Impact factor: 5.790

9.  Multicenter implementation of a severe sepsis and septic shock treatment bundle.

Authors:  Russell R Miller; Li Dong; Nancy C Nelson; Samuel M Brown; Kathryn G Kuttler; Daniel R Probst; Todd L Allen; Terry P Clemmer
Journal:  Am J Respir Crit Care Med       Date:  2013-07-01       Impact factor: 21.405

Review 10.  Clinical implications of positive blood cultures.

Authors:  C S Bryan
Journal:  Clin Microbiol Rev       Date:  1989-10       Impact factor: 26.132

  10 in total

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